Adaptive Exponential Functional Link Network (AEFLN)

Nonlinear System Identification using Adaptive Exponential Functional Link Network (AEFLN) Based Adaptive Filter, A #Generic Code

In this code, we will identify a nonlinear system using the most recent adaptive exponential functional link network (AEFLN)-based adaptive filter. These type of filters belong to a class of linear-in-the-parameters nonlinear adaptive filters. This filter is first proposed by our group leading by Prof. Nithin V. George at Indian Institute of Technology Gandhinagar. Details can be found in the following paper:

V. Patel, V. Gandhi, S. Heda, and N. V. George, “Design of Adaptive Exponential Functional Link Network-Based Nonlinear Filters,” IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 63, no. 9, pp. 1434–1442, 2016.

Similar to my previous TFLN and Volterra filter codes, in this experiment, we have used this filter in a nonlinear system identification scenario, where the nonlinearity is introduced by the loudspeaker. For more details, please refer to the example 1 (Case I of page 5) of the above paper. All the parameters used in this code are in coordinance with the parameters used in the above example.

The code is nicely scripted. Hope this helps!!!!!